Edge Detection Based on the Gradient Operators Optimized by Genetic Algorithms

Computer image processing technology has been widely used in various image test,pattern recognition and computer vision,and edge detection is one of the fundamental steps on the lowest level of image processing.Due to the affection of the noise and unbalanced light source,no method can detect the edges of all modals.There fore, an approach based on gray level's gradient operators and genetic algorithm was proposed in this paper.This approach can optimize the gray level’s gradient operators by genetic algorithm,and the fitness function of the genetic algorithms is the least square error criterion used in the procedure of supervised training.The proposed method can obtain the optimal edge detector for the image modal of training set.The optimized gradient operators present good performance in lower SNR and make the detected edges more precise.